A Novel Approach for Prediction of the Lung Disease using Deep Learning

The application of cutting-edge technologies in caused by the unwanted thickening of the areas in the lungs which can due to fibrosis), pneumonia (a condition where the alveoli or sacs in one or both of healthcare has the potential to transform diagnostic capacities and enhance patient care. This research investigates how deep learning and mobile app development may work together in analyzing X-ray images to detect lung problems. With the help of Flutter’s adaptability and Convolutional Neural Networks’ (CNNs) capability, the proposed system enables real-time X-ray image processing on mobile devices. The proposed solution provides a user-friendly tool for accurate diagnosis and prompt intervention to healthcare practitioners with effective data preprocessing, model training, and interaction with the Flutter framework. Beyond its current deployment, the future scope of this study includes the potential for additional improvement, growth into other medical imaging modalities, and integration with cloud-based healthcare systems. By applying more innovation and collaboration, digital technology can improve healthcare outcomes and enhance the well-being of patients across the globe.